COSMOLOGY AND HINDU THOUGHT

Abstract. This paper outlines some major ideas concerning cosmogony and cosmogony and cosmology that pervade the Hindu conceptual world. The basic source for this discussion is the philosophical literature of some of the principal schools of Hindu thought, such as VaiVaiśika, Sānkhya, and Advaita Vedānta, focusing on the themes of cosmology, time, and soteriology. The core of Hindu philosophical thinking regarding these issues is traced back to the Rk Vedic cosmogonical speculations, analyzed, and contrasted with the "views of the opponent." The relevance of the Hindu worldview for overcoming the conflict between science and religion is pointed out.     

A probabilistic model of theory formation

Concept learning is challenging in part because the meanings of many concepts depend on their relationships to other concepts. Learning these concepts in isolation can be difficult, but we present a model that discovers entire systems of related concepts. These systems can be viewed as simple theories that specify the concepts that exist in a domain, and the laws or principles that relate these concepts. We apply our model to several real-world problems, including learning the structure of kinship systems and learning ontologies. We also compare its predictions to data collected in two behavioral experiments. Experiment 1 shows that our model helps to explain how simple theories are acquired and used for inductive inference. Experiment 2 suggests that our model provides a better account of theory discovery than a more traditional alternative that focuses on features rather than relations.     

“SCIENCE–RELIGION SAMVADA” AND THE INDIAN CULTURAL HERITAGE

This article seeks to delineate some of the fundamental philosophical traits that are special characteristics of the Indian cultural soil. Tracing these from the Vedic period, it is shown that this heritage is still alive and gives a distinctive flavor to the science–religion dialogue in the Indian context. The prevalent attitude is not to view science and religion as antagonistic, but rather as forces that together could create a world where the persistent epistemological and ethical problems can get resolved to the benefit of humanity. In Indian thought rationality and spirituality are not viewed as opposed categories. The notion of “evidence” has played a crucial role in all enquiries for legitimizing the sources of knowledge and the criteria by which any claim to knowledge can be tested. References to investigations pertaining to such areas as cosmology, ecology, ethics, study of consciousness, and so on are made in order to bring out their relevance for science–religion dialogue today.     

Acquisition of decision making criteria: reward rate ultimately beats accuracy

Speed-accuracy trade-offs strongly influence the rate of reward that can be earned in many decision-making tasks. Previous reports suggest that human participants often adopt suboptimal speed-accuracy trade-offs in single session, two-alternative forced-choice tasks. We investigated whether humans acquired optimal speed-accuracy trade-offs when extensively trained with multiple signal qualities. When performance was characterized in terms of decision time and accuracy, our participants eventually performed nearly optimally in the case of higher signal qualities. Rather than adopting decision criteria that were individually optimal for each signal quality, participants adopted a single threshold that was nearly optimal for most signal qualities. However, setting a single threshold for different coherence conditions resulted in only negligible decrements in the maximum possible reward rate. Finally, we tested two hypotheses regarding the possible sources of suboptimal performance: (1) favoring accuracy over reward rate and (2) misestimating the reward rate due to timing uncertainty. Our findings provide support for both hypotheses, but also for the hypothesis that participants can learn to approach optimality. We find specifically that an accuracy bias dominates early performance, but diminishes greatly with practice. The residual discrepancy between optimal and observed performance can be explained by an adaptive response to uncertainty in time estimation.